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Everything about Approximate Bayesian computation
Computational method in Bayesian statistics
Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics that can be used to estimate the posterior distributions of model parameters. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Approximate Bayesian computationA 5-minute orientation
- Skim a recent paper: pyABC: Efficient and robust easy-to-use approximate Bayesian computationInfluential work since 2022
- Pick up a classic book: Artificial intelligenceThe most-reprinted book on the subject
- Read the landmark paper: Approximate Bayesian Computation in Population GeneticsCited 2,525 times
- Go sideways: Bayesian statisticsA closely related topic
- Go sideways: Bayesian inferenceA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Approximate Bayesian Computation in Population Genetics
Approximate Bayesian Computation (ABC) in practice
Approximate Bayesian Computation in Evolution and Ecology
Approximate Bayesian Computation
Adaptive approximate Bayesian computation
Constructing Summary Statistics for Approximate Bayesian Computation: Semi-Automatic Approximate Bayesian Computation
Non-linear regression models for Approximate Bayesian Computation
A tutorial on approximate Bayesian computation
🆕 Influential since 2022
pyABC: Efficient and robust easy-to-use approximate Bayesian computation
Dark energy by natural evolution: Constraining dark energy using Approximate Bayesian Computation
Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation
A generic stochastic hybrid car-following model based on approximate Bayesian computation
Guided wave-based characterisation of cracks in pipes utilising approximate Bayesian computation
📚 Books worth reading
Artificial intelligenceStuart J. Russell, Peter Norvig · 1994
Neural Information ProcessingTingwen Huang · 2012
Communications, Signal Processing, and SystemsQilian Liang · 2012
Statistical Atlases and Computational Models of the Heart. Imaging and Modelling ChallengesOscar Camara · 2012
The Elements of Statistical LearningTrevor Hastie, Robert Tibshirani · 2001- 📕Bayesian time series modelsDavid Barber, Ali Taylan Cemgil · 2011
The Jackknife and BootstrapJun Shao, Dongsheng Tu · 1995
Introduction to Multiple Time Series AnalysisHelmut Lütkepohl, Helmut Lutkepohl · 1991
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
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